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Record W2110932818 · doi:10.2308/aud.2001.20.2.101

The Audit Retention Decision in the Face of Deregulation: Evidence from Large Private Canadian Corporations

2001· article· en· W2110932818 on OpenAlexaffabout
David Senkow, Morina Rennie, Richard D. Rennie, Jonathan Wong

Bibliographic record

VenueAuditing A Journal of Practice & Theory · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsVancouver Biotech (Canada)University of Regina
Fundersnot available
KeywordsAuditAccountingLegislationBusinessContext (archaeology)Joint auditAudit evidenceDeregulationFinancial AuditExternal auditorInternal auditFinanceEconomicsLawPolitical science

Abstract

fetched live from OpenAlex

We examine the demand for audited financial statements in the context of deregulation. In 1994 a change in Canadian legislation eliminated a mandatory requirement for certain private companies to file audited financial statements. The objective of this research was to determine the importance of factors that might influence whether the audit is discontinued. Information was obtained from the Cancorp Plus database and through a survey of companies affected by the change in legislation. It was found that a large majority of the companies retained their audit. The strongest predictors of whether the audit would be retained were the prior existence of a lending agreement requiring audited financial statements and the level of audit fees. The likelihood of retention was positively related to the magnitude of fees, perhaps reflecting the perceived benefits of the audit. The existence of a lending agreement was found to be influenced by the ownership level of the entity's officers and directors. This study underlines the importance of audited financial statements to lenders.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.261
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations41
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueAuditing A Journal of Practice & TheorySame topicAuditing, Earnings Management, GovernanceFrench-language works237,207